Open source hybrid-search projects
Every project in the registry tagged hybrid-search, ranked by real GitHub adoption.
Lightning-fast search for your applications
Fast, scalable vector database for AI applications
AI-native vector database for intuitive applications
One Postgres for your application data, full-text search, vector retrieval, and aggregations. Home of the pg_search extension.
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
Full-text search API with real-time indexing and crawling
Related tags
Frequently asked questions
How many open source hybrid-search projects are there?
This registry tracks 6 projects tagged hybrid-search, with 126,668 GitHub stars between them. The most-adopted is Meilisearch at 59,317 stars.
Are these hybrid-search projects free to use?
Yes — 4 of the 6 carry an explicit open-source licence across 2 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which hybrid-search project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these hybrid-search projects still maintained?
6 of the 6 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.